Wafer or reticle defect inspection systems with capability of defect classification have been widely used in semiconductor manufacturing. With the technology progressing into finer resolutions such as beyond 20 nm, increasing number of defects can be caused by various system conditions, e.g., process variation, and OPC techniques. The ever-increasing systematic defects can lead to lower performances.
Machine learning techniques can be used for defect classification. However, increasing number and data size of defects can cause performance deterioration, such as lower accuracy or longer processing time.